Computing and electronic devices rely on memory devices to store data and code for their various functions. As computing devices have increased in computational performance, they have included more and more storage and memory to meet the needs of the programming and computing performed on the devices. In mobile computing devices, controlling power consumption is a key design focus. Memory devices and memory subsystems consume a significant amount of total power consumption in low power and other mobile devices.
Power management of memory devices has traditionally been performed as an open loop process, relying on table of memory device “weights” generated from the device manufacturers. One traditional approach to power management is RAPL (running average power limit), which employs such an open loop process. Computing devices include the tables in initialization systems and project worst case memory power scenarios and power regulation strategies based on the tables. It will be understood that the tables indicate ranges and/or worst case performance parameters, without any way to account for the performance parameters of a specific memory device. Thus, the memory power projections will typically over-predict actual power, but could also fail to predict sufficient power usage for outlier parts. The over-prediction of power can result in a system performing under its optimal level for the power consumption allowed. The failure to predict outlier parts could cause overheating in the platform and/or failure.
Descriptions of certain details and implementations follow, including a description of the figures, which may depict some or all of the embodiments described below, as well as discussing other potential embodiments or implementations of the inventive concepts presented herein.